class_docstr: Calculates the values of a set of features for given instance ids.
code: def _calculate_features(
      self, df, df_trie, features, progress_callback
  ):
      # Group the features so that each group can be calculated together.
      # The groups must also be in topological order (if A is a transform of B
      # then B must be in a group before A).
      feature_groups = self.feature_set.group_features(features)
  
      for group in feature_groups:
          representative_feature = group[0]
          handler = self._feature_type_handler(representative_feature)
          df = handler(group, df, df_trie, progress_callback)
  
      return df
  
imports: from datetime import datetime
  from functools import partial
  import numpy
  import pandas
  import pandas.api.types
  from featuretools.entityset.relationship import RelationshipPath
  from featuretools.exceptions import UnknownFeature
  from featuretools.feature_base import AggregationFeature, DirectFeature, GroupByTransformFeature, IdentityFeature, TransformFeature
  from featuretools.utils import Trie
  from featuretools.utils.gen_utils import Library, get_relationship_column_id, import_or_none, is_instance
label_desc: Use image node_id 4 for calling the FeatureSetCalculator obj's underlying member method code with example usage: obj._calculate_features(df, df_trie, features, progress_callback) and returns: df